SOTAVerified

Graph Generation

Graph Generation is an important research area with significant applications in drug and material designs.

Source: Graph Deconvolutional Generation

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 201–210 of 712 papers

TitleStatusHype
Resistance Training using Prior Bias: toward Unbiased Scene Graph GenerationCode1
Fast Graph Generation via Spectral DiffusionCode1
Linguistic Structures as Weak Supervision for Visual Scene Graph GenerationCode1
Leveraging Predicate and Triplet Learning for Scene Graph GenerationCode1
Fine-Grained Evaluation of Large Vision-Language Models in Autonomous DrivingCode1
Context-Aware Scene Graph Generation With Seq2Seq TransformersCode1
Spatial-Temporal Knowledge-Embedded Transformer for Video Scene Graph GenerationCode1
Optimized Crystallographic Graph Generation for Material ScienceCode0
Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion ModelsCode0
On-Demand and Lightweight Knowledge Graph Generation -- a Demonstration with DBpediaCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1RNNStreetMover0.03—Unverified
2GraphRNNStreetMover0.02—Unverified
3GGT without CAStreetMover0.02—Unverified
4GGTStreetMover0.02—Unverified